Nanobiosensors for point-of-care medical diagnostics 9811951403, 9789811951404

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Nanobiosensors for Point-of-Care Medical Diagnostics Manashjit Gogoi Sanjukta Patra Debasree Kundu Editors

Nanobiosensors for Point-of-Care Medical Diagnostics

Manashjit Gogoi • Sanjukta Patra • Debasree Kundu Editors

Nanobiosensors for Point-of-Care Medical Diagnostics

Editors Manashjit Gogoi Department of Biomedical Engineering North-Eastern Hill University Shillong, Meghalaya, India

Sanjukta Patra Department of Biosciences and Bioengineering Indian Institute of Technology Guwahati, Assam, India

Debasree Kundu Department of Biosciences and Bioengineering Indian Institute of Technology Guwahati, Assam, India

ISBN 978-981-19-5140-4 ISBN 978-981-19-5141-1 https://doi.org/10.1007/978-981-19-5141-1

(eBook)

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

With rapid urbanization, increase in human life expectancy and environmental pollution, people are more susceptible to various diseases. So, the cost of healthcare is increasing at an alarming rate. Early diagnosis plays an important role in curing and managing many life-threatening diseases. For instance, chances of curing cancer increase when detected at an early stage. In the case of diabetic patient, detection of glucose level at regular intervals is important for its proper management. Conventional detection methods or techniques and equipment are limited to established hospitals or sophisticated laboratory setup. These facilities are expensive and need properly trained manpower for operation. These facilities are hardly available in the rural areas putting limitations on diagnostic confirmations. Emergent of situation, like Covid-19 pandemic where healthcare infrastructures are overburdened, manpower are overstressed, the use of point-of-care (POC) biosensors is of great help. Biosensors draw huge attention due to ease of application, high sensitivity, high selectivity, low cost, and low turnaround time. They help in non-invasive or minimally invasive, diagnosis of diseases. Point-of-care biosensors are the translated version of biosensor knowledge base. Even though the field of biosensors has been increasing rapidly, there is a huge gap between the existing knowledge base and their translation into working POCs. Understanding the reasons behind this gap will motivate more people to work towards filling this existing gap. Chapter 1 focusses on the application of POC biosensors for healthcare applications and how they are helping in curbing disease transmission/treatment and management of different diseases. It also gives an overview of existing commercial biosensors available in the market. Chapter 2 reviews the application of different biomolecules used in POC biosensors. It also highlights the design and applications of various biomolecules with the aim of addressing the existing challenges in POC biosensors in healthcare diagnostics. Chapter 3 highlights different nanomaterials used for the development of POC biosensors along with their challenges and future prospects.

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Chapter 4 discusses new generation molecular techniques used in POC biosensors for the detection of infectious. This chapter elaborates various advantages and pitfalls of molecular methods in colorimetric, electrochemical, fluorescence, magnetic, chemiluminescence, surface plasmon resonance (SPR), and surface-enhanced Raman scattering (SERS)-based POC biosensors that have led to the development of miniaturized lab-on-a-chip (LOC) devices are discussed. Chapter 5 elaborates on POC biosensors for glucose sensing. This chapter also highlights the challenges and future prospects in glucose sensing biosensors. Chapter 6 focusses on several combinations of affordable POC equivalents that are alternative to cumbersome and traditional diagnostic tests that have been proven to be effective in emergency healthcare. Analysis of the time-saving benefit to cost ratio is crucial to improve the overall processing of a cancer patient culminating in decreased turnaround times as well as quicker diagnosis leading to rapid patient disposition. Chapter 7 elucidates a wide range of POC diagnostic platforms used for diagnosis of the cardiovascular diseases using different biochemical biomarkers. These POC platforms have a promising impact on the early prediction and diagnosis of the future of cardiac care. Chapter 8 discusses different POC nanobiosensors for determining vitamin deficiency which is affecting people of all ages. The chapter also explains how these devices can help primary care practitioners and general physicians to detect vitamin deficiencies and optimize vitamin supplementation doses. Chapter 9 presents recent POC biosensors for the diagnosis of neurological disorders and how nanoparticles can be used for their efficient diagnosis and progressions. Chapter 10 provides update about POC biosensors for sexually transmitted diseases and how the advancement of POC biosensors improves the recovery rate, decreases the complications of these diseases, and benefits the public health of societies by breaking the chain of disease transmission. Chapter 11 elucidates about recent advancement of microfluids-based nanobiosensors and their potential as well as challenges in healthcare sector. Chapter 12 presents an overview about recent advancement on nanobiosensors in disease diagnosis and their potential in early diagnosis and treatments. In nutshell, this book depicts the current status and future prospects of POC biosensors for healthcare applications. The chapters deal with the basics of POC biosensors, nanomaterials used for the biosensor, and applications of the biosensors for the detection of different diseases. The target group of the book is post-graduate, PhD students, and advanced researchers. It will be helpful for both novices and the experts working in the field of biosensors. Shillong, Meghalaya, India Guwahati, Assam, India Kharagpur, West Bengal, India

Manashjit Gogoi Sanjukta Patra Debasree Kundu

Acknowledgement

First of all, the editors would like to thank the almighty God for proving us with the motivation and strength to complete this endeavour of editing this book. The editors would like to sincerely thank Dr. Bhavik Sawhney, Editor, Biomedicine, and all the board members from Springer Nature for their approval and for granting us this opportunity to edit this book. We would like to express our sincere gratitude to Ms. Vaishnavi Venkatesh, Project Coordinator (Books), Springer Nature, for constantly following up on the editing process and helping us to complete this assignment. The editors express their heartfelt gratitude to all the contributors of this book for their contributions. Their contributions are sincerely appreciated and gratefully acknowledged. Dr. Manshjit Gogoi expresses his thankfulness to his beloved sons Aditya, Atanu, wife Mayuri, who sacrificed a lot and kept him inspired to finish this task. He is also thankful to his sister-in-law Hewali, and his parents, brothers, and in-laws for their constant support, unconditional love, and encouragement. Prof. Sanjukta Patra expresses heartfelt thankfulness to little Paridhi. It is her shared time which has brought this book in black and white. The motivation of her husband Rajesh has shown her the way forward. The support of her parents and parents-in-law has kept her moving ahead. Dr. Debasree Kundu expresses her sincere gratitude to her husband and family members for their constant support and motivation.

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Contents

1

Point-of-Care Biosensors for Healthcare Applications . . . . . . . . . . . Bethuel Daurai and Manashjit Gogoi

2

An Overview of Biomolecules Used in the Development of Point-of-Care Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Girish Chandra Mohanta and Satish Kumar Pandey

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Nanomaterials for Point-of-Care Biosensors . . . . . . . . . . . . . . . . . . Sourav Sarkar, Mrityunjoy Mahato, and Manashjit Gogoi

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New-Generation Molecular Techniques in POC Biosensors for Detection of Infectious Diseases . . . . . . . . . . . . . . . . . . . . . . . . . Aaydha Chidambara Vinayaka, Than Linh Quyen, Mohsen Golabi, Trieu Nguyen, Van Ngoc Huynh, Dang Duong Bang, and Anders Wolff

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Point-of-Care Biosensors for Glucose Sensing . . . . . . . . . . . . . . . . . 107 Tanmay Vyas, Sandeep Choudhary, Nikhil Kumar, and Abhijeet Joshi

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Overview of Affordable Upfront Point-of-Care Testing for Cancer Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Subodh Kumar, Satish Kumar Pandey, Phulen Sarma, Anusuya Bhattacharyya, Hardeep Kaur, Manisha Prajapat, Amit Raj Sharma, Saniya Mahendiratta, Girish Chandra Mohanta, Ajay Prakash, and Bikash Medhi

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Point-of-Care Diagnostic Testing in Urgent Cardiac Care . . . . . . . . 155 Neelam Vishwakarma, Satish Pandey, and Suman Singh

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Point-of-Care Nanobiosensors for Determining Vitamin Deficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Hrishikesh Kalita, Mahima Kumari, Mayank Bhushan, Debananda Mohapatra, and Laishram Robindro Singh ix

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Utility of Nanobiosensors as a Point-of-Care Diagnostics for Neurological Disorders: From Bench to Bedside . . . . . . . . . . . . . . . 195 Amit N. Raju, Aliabbas A. Husain, and Rajpal S. Kashyap

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Point-of-Care Testing and Diagnostics for Sexually Transmitted Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Vinod Kumar and Prabhjot Kaur

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Nanobiosensor-Based Microfluidic Point-of-Care Platforms: Fabrication, Characterization, and Applications . . . . . . . . . . . . . . . 233 Nimisha Roy, Sonal Jaiswal, Amar Dhwaj, Deepti Verma, and Amit Prabhakar

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Nanobiosensor: Advancement in Disease Diagnostic . . . . . . . . . . . . 257 Shubham Arunrao Chinchulkar, Sri Amrutha Sankaranarayanan, and Aravind Kumar Rengan

Editors and Contributors

About the Editors Manashjit Gogoi is working as an Assistant Professor in the Department of Biomedical Engineering, North-Eastern Hill University, Shillong, since last 10 years. He did his PhD in Biomedical Engineering from Indian Institute of Technology, Bombay, Mumbai. His research area focusses on Bio-nanotechnology and its application in healthcare diagnostic and therapeutics. He is an erudite researcher and is presently undertaking 04 research projects from various funding agencies. He has to his credit 19 research articles, 20 book chapters, and 01 patent (filed). He has actively supervised PhD (02 completed and 03 undergoing) students. He served as Section Editor of Current Pathobiology Reports (2020–2021) published by Springer for a special issue on ‘Nano drug delivery’ and is a member of several scientific associations. His commendable efforts in exploiting nanocarriers for cancer therapy help to realize his true potential for serving the scientific interests in the field of healthcare. Sanjukta Patra is working in the Department of Biosciences and Bioengineering at the Indian Institute of Technology Guwahati, Assam, India, since last 13 years and is also heading the School of Agro and Rural Technology of the Institute. She has earned her PhD in Biotechnology from Central Food Technological Research Institute, Mysuru. Her PhD thesis encompassed study of microbial and enzymatic biotransformation of coffee and tea processing wastes. She has expertise in enzyme engineering, enzymes in biosensors, enzymatic remediation, applied microbiology, and environmental microbiology. Presently, she has a dedicated research group of ‘Enzyme and Microbial Technology’, where her team is working towards diverse aspects of enzymes, the challenges in enzymatic process and its applications. She is also the course instructor for graduate and post-graduate students. She has actively supervised several PhD (07 completed and 12 undergoing) and various MTech (14) students towards different aspects of enzymes and its applications. Her undaunted enthusiasm and research intellect enabled her to have patents (03 granted), xi

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International project (01), and National projects (12) to her credit. Till date, she has published 51 international peer-reviewed research articles and have authored 17 book chapters. She has consistent research penchant on enzymes that helps to catapult her research instinct. Debasree Kundu is working as Women Scientist in the Department of Biotechnology at the Indian Institute of Technology Kharagpur, West Bengal, India. Prior to this, she was associated with the Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Assam, India, where she was pursuing her post-doctoral research and worked towards unravelling the mechanistic insights into pesticides-induced adaptive response in microbes using proteomic approaches. She has co-supervised several post-graduate dissertations pertaining to enzyme responsive nanoparticles for drug delivery and therapeutic applications. She has nurtured her research instincts that prompted her to have 31 (21 research articles and 10 review articles in edited books) peer-reviewed research publications. She has also granted patent to her credit. She has made sincere efforts and maintained consistency towards her research endeavour of enzymatic biotechnology and interdisciplinary research interests.

Contributors Dang Duong Bang Laboratory of Applied Micro and Nanotechnology (LAMINATE), Department of Bioengineering, Technical University of Denmark, Kgs Lyngby, Denmark Anusuya Bhattacharyya Department of Ophthalmology, GMCH-32, Chandigarh, India Mayank Bhushan Department of Nanotechnology, North-Eastern Hill University, Shillong, Meghalaya, India Shubham Arunrao Chinchulkar Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Sangareddy, Kandi, Telangana, India Sandeep Choudhary Department of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India Bethuel Daurai Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India Amar Dhwaj Department of Applied Science, Indian Institute of Information Technology Allahabad, Allahabad, Uttar Pradesh, India Manashjit Gogoi Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India

Editors and Contributors

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Mohsen Golabi Laboratory of Applied Micro and Nanotechnology (LAMINATE), Department of Bioengineering, Technical University of Denmark, Kgs Lyngby, Denmark Aliabbas A. Husain Research Centre, Central India Institute of Medical Sciences, Nagpur, Maharashtra, India Van Ngoc Huynh Biolabchip Group, Department of Bioengineering, Technical University of Denmark, Kgs Lyngby, Denmark Sonal Jaiswal Department of Applied Science, Indian Institute of Information Technology Allahabad, Allahabad, Uttar Pradesh, India Abhijeet Joshi Department of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India Hrishikesh Kalita Department of Nanotechnology, North-Eastern Hill University, Shillong, Meghalaya, India Rajpal S. Kashyap Research Centre, Central India Institute of Medical Sciences, Nagpur, Maharashtra, India Hardeep Kaur Department of Pharmacology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Prabhjot Kaur Department of Nephrology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Mahima Kumari Department of Zoology, Jai Prakash University, Chapra, Bihar, India Nikhil Kumar School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India Subodh Kumar Department of Pharmacology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Vinod Kumar Department of Dermatology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Quyen Than Linh Biolabchip Group, Department of Bioengineering, Technical University of Denmark, Kgs Lyngby, Denmark Mrityunjoy Mahato Department of Basic Sciences and Social Sciences, NorthEastern Hill University, Shillong, Meghalaya, India Saniya Mahendiratta Department of Pharmacology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Bikash Medhi Department of Pharmacology, Postgraduate Institute for Medical Education and Research, Chandigarh, India

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Editors and Contributors

Girish Chandra Mohanta Material Science and Sensor Applications (MSSA) Division, CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh, India Debananda Mohapatra School of Chemical Engineering, Yeungnam University, Gyeongsan, Gyeongbuk, Republic of Korea Trieu Nguyen Biolabchip Group, Department of Bioengineering, Technical University of Denmark, Kgs Lyngby, Denmark Satish Kumar Pandey Department of Biotechnology, School of Life Sciences, Mizoram University (Central University), Aizawl, Mizoram, India Amit Prabhakar Department of Applied Science, Indian Institute of Information Technology Allahabad, Allahabad, Uttar Pradesh, India Manisha Prajapat Department of Pharmacology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Ajay Prakash Department of Pharmacology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Amit N. Raju Research Centre, Central India Institute of Medical Sciences, Nagpur, Maharashtra, India Aravind Kumar Rengan Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Sangareddy, Kandi, Telangana, India Nimisha Roy Department of Applied Science, Indian Institute of Information Technology Allahabad, Allahabad, Uttar Pradesh, India Sri Amrutha Sankaranarayanan Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Sangareddy, Kandi, Telangana, India Sourav Sarkar Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India Phulen Sarma Department of Pharmacology, AIIMS, Mangalgiri, Andhra Pradesh, India Amit Raj Sharma Department of Pharmacology, Postgraduate Institute for Medical Education and Research, Chandigarh, India Laishram Robindro Singh Department of Nanotechnology, North-Eastern Hill University, Shillong, Meghalaya, India Suman Singh CSIR - Central Scientific Instruments Organisation, Chandigarh, India Academy of Scientific and Innovative Research, Ghaziabad, India Deepti Verma Department of Chemistry, University of Allahabad, Prayagraj, Uttar Pradesh, India

Editors and Contributors

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Aaydha Chidambara Vinayaka Laboratory of Applied Micro and Nanotechnology (LAMINATE), Department of Bioengineering, Technical University of Denmark, Kgs Lyngby, Denmark Neelam Vishwakarma CSIR - Central Scientific Instruments Organisation, Chandigarh, India Academy of Scientific and Innovative Research, Ghaziabad, India Tanmay Vyas Department of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India Anders Wolff Biolabchip Group, Department of Bioengineering, Technical University of Denmark, Kgs Lyngby, Denmark

Chapter 1

Point-of-Care Biosensors for Healthcare Applications Bethuel Daurai and Manashjit Gogoi

1.1

Introduction

Biosensor is a device that detects chemical molecules via biochemical processes mediated by enzymes, immunosystems, tissues, organelles, or entire cells, generally using electrical, thermal, or optical signals (Monošík et al. 2012; Turner 2013, 2014; Jurado-Sánchez 2018). Biosensors are composed of bioreceptors, transducers, and an electronic processing unit (containing a signal processing unit and a display system). Bioreceptors or recognition elements are immobilized biological molecules like enzyme, substrate, complementary DNA, and antigen which detect or sense target analytes based on their affinity (Davis et al. 1995; Abd El-Hamid et al. 2015; Senbua et al. 2020). The transducer converts biochemical signal into an electrical signal as a consequence of the analyte’s interactions with the bioreceptor. The strength of the signal produced by the biological reaction is proportional to the concentration of the analyte (Arkin and Ross 1994; Nikhil et al. 2016). The electrical signal is subsequently translated into a readable value for the analyte concentration by the signal processing unit, which consists of a microcontroller. A display system will then be integrated to display useful information of the analyte. The use of a signal processing unit allows the use of mathematical models for further analysis, storage, and transfer of the results and data. The schematic representation is given in Fig. 1.1. Point-of-care (POC) biosensors are scaled down to compact device or equipment that quantifies or qualifies certain analytes for the determination of diseases and ailment conditions (Gouvêa 2011; Soler et al. 2019) near the patient. POC biosensor helps a person to analyse samples without a sophisticated instrument or an expert (Luppa et al. 2011). A blood glucose system is one of the greatest examples of a POC

B. Daurai · M. Gogoi (*) Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 M. Gogoi et al. (eds.), Nanobiosensors for Point-of-Care Medical Diagnostics, https://doi.org/10.1007/978-981-19-5141-1_1

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Fig. 1.1 Schematic diagram of a biosensor where an analyte binds to a bioreceptor which is then translated into a readable signal by a transducer

gadget that uses an electrochemical detection process. It is now widely used in household for a diabetic patient (Newman and Turner 2005). POC testing shortens the therapeutic turnaround time (TTAT), i.e. the time between placing an order for a test and receiving an order for therapy (Fermann and Suyama 2002). POC test depends on several factors like regulatory standard, the cost-effectiveness and ease of using the device. POC testing needs proper and regular validation by regulatory boards with strict criteria to meet the standard of a laboratory test (Lippi et al. 2013). There is also a requirement of integrating the results of POC testing with laboratory information system and hospital information system. POC testing requires less quantity of sample to give accurate and rapid results which improves the quality and efficiency of care in an emergency service, operation room, critical care, and in outpatient setting (Kost et al. 1999; Larsson et al. 2015). Rapid diagnostic tests (RDT) are also useful in the healthcare perspective as they can give qualitative results in a matter of seconds which are important in times of an epidemic (Gavin and Thomson Jr 2004). POC devices could be characterized for clinical investigation at or close to the area of patient consideration. The main objective of POC device is to give quick and simple result from an analytic test that shortens the time taken when compared with a test done in laboratory equipments and highly trained professionals (Arefin et al. 2017; Brazaca et al. 2017; Harris et al. 2017). POC biosensors have a number of unique requirements. The device should give quick result in an emergency clinic or primary healthcare centres where sophisticated facilities are not available readily (Tiwari 2010). Storage should be possible at room temperature or in an ordinary refrigerator. Miniaturization is also an important part in a POC biosensor (Liu et al. 2020). Smaller devices are easier to carry and helpful for POC applications. Wearable biosensors (WB) are non-invasive natural sensors incorporated into different wearables, for example, watches, garments, gauzes, glasses, contact focal points, rings, etc. (Ghafar-Zadeh 2015). WB can also be a POC testing element as

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they can often be used to determine the physical parameters like blood oxygen saturation, heart rate and even electrocardiogram data can now be collected on the move using non-invasive mode (Arefin et al. 2017).

1.2

Biosensors for POC Testing

One of the most significant utilizations of biosensors is the POC testing. POC testing is the act of playing out a demonstrative or prognostic test close to the patient to give fast outcomes, which means the test itself must be fast and effortlessly performed without the utilization of costly and complicated instrumentation (Baryeh et al. 2017). Microfluidic-based biosensor provides platform for cell growth and analysis of the samples. Most platforms used for microfluidics are based on PDMS, paper, silicone, and polymer (Pandey et al. 2018). Filter paper and nitrocellulose membrane are cost-effective and have been widely used in laminar flow type of biosensor for mainly qualitative analysis. Lab-on-chip (LOC), a miniaturized version of a lab made from PDMS, paper, and paraffin pellets are one of the platforms of affordable POC biosensor (Kumar et al. 2013; Patel et al. 2016). They are specifically designed for resource-limited settings where only the biological samples are sufficient to do the tests (Zarei 2017). LOC biosensors are labelled because the bioreceptors and other transducers are used to get the desired signal. The label-free type of biosensors are more advantageous for POC testing as the analyte themselves acts like a transducer to get the desired signal (Cooper 2003; Baryeh et al. 2017). Several nanomaterials including gold nanoparticle (AuNP), quantum dots (QD), carbon nanotube (CNT), silica nanoparticles (SiNP), and graphene are used in POC biosensors. These nanoparticles are employed in biosensors to increase the biosensors’ sensitivity, reliability, and responsiveness (Brazaca et al. 2017). Nanomaterials have a high surface area to volume ratio; however, they have drawbacks such as toxicity, loading capacity limitations, and particle aggregation. Moreover, multi-layered structures of paper are also used as a microfluidic channel by restricting areas of paper with hydrophobic material. Biomarkers determine the accuracy and resolution of the analyte detection technique. Based on the design and usage, POC biosensors can be categorised as a handheld device (which may consist of an electronic component) and a tabletop/benchtop device which can be as big as a portable autoanalyser. Handheld POC biosensors can be as simple as a cassette-based test strip, or it can have an electronic component with display of results. Rapid diagnostic tests (RDT) provide results in as little as a few seconds to a few hours, depending on the test. Figure 1.2 is a typical cassette for rapid tests that gives qualitative analysis of the analyte. It works on the principle of lateral flow immunochromatographic assay (LFIA). Some common examples of RDT/LFIAs done are pregnancy test, malarial test, test for coronavirus disease 2019, and some other viral diseases like influenza. Most RDTs are qualitative in

4 Fig. 1.2 A typical RDT/LFIA cassette where the change in colour of the test line indicates the presence of the specific analyte of specific quantity

B. Daurai and M. Gogoi Round Hole for buffer

Square hole For Blood Result Window

‘T’ Test Line ‘C’ Control Line

determining the disease. There are some diseases that require the quantification of the analyte. RDT of certain diseases and conditions are already available in the market for end users. Pregnancy test kit, a POC (RDT) device in India, is available in a variety of brands most of them working with the same principle of immunochromatography method with minor modifications to detect hCG hormone in the urine. Some of them are Prega News by Mankind Pharmaceutical Ltd., i-can by Piramal Healthcare, Velocit by Dr. Reddy’s, etc. There are many other rapid test kits using biosensor and chromatography like rheumatoid factor, Widal (salmonella typhi and paratyphi), dengue NS1 antigen, dengue IgG/IgM, C-reactive protein, and even HIV. Although these POC tests provide rapid and precise findings, laboratory procedure and validation with a polymerase chain reaction (PCR) or enzyme-linked immunosorbent assay (ELISA) will always remain the gold standard. Figure 1.3 shows a typical rapid diagnostic device with a cassette. Rapid test biosensors can also have complicated electronic systems to detect analytes using an electrochemical sensing process. For example, a handheld POC biosensor determines the amylase level in saliva to determine the stress level in patients (Yamaguchi et al. 2006). This kind of kit does not require any expert professional to test. Blood glucose analysers are widely used in handheld POC rapid test systems that work using an electrochemical sensing process. OneTouch, Accu chek, TrueTrack, and Omnitest are some lines of devices that are used in testing blood glucose. Benchtop POC biosensor for troponin I by Pathfast (Mitsubishi Chemica) is equivalently effective as the FDA-approved laboratory test (Peacock et al. 2016). Benchtop devices are bigger in size than a handheld device. A better option is available in order to make it portable and POC. Augustine et al. reported using an autoanalyser as a point-of-care haemoglobin test, although the cost of the autoanalyzer is very high (Augustine et al. 2020).

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Fig. 1.3 (a) Handheld α-amylase tester from saliva. (b) Sample collection from saliva using paper (Yamaguchi et al. 2006)

1.3

Application of POC Biosensors in Healthcare

POC biosensor in the healthcare system reduces the TTAT. All diseases have biomarkers in one or more biological fluids or materials (Griffiths et al. 2002; Strimbu and Tavel 2010). A qualitative or quantitative analysis of these biomarkers will identify the disease. Based on this, biosensors for POC testing are designed to get a better TTAT (Mayeux 2004). Many POC biosensors are already available for various diseases like cardiovascular diseases, pancreatic disease, kidney disease, neurological problem, diabetes, urinary tract infection, etc. We discuss some of the diseases, their biomarkers, and the POC biosensors available for the biomarkers. A survey conducted by Satyanarayana et al. from various primary healthcare providers in India showed that the most used POC tests are pregnancy test followed by malaria, glucose, HIV, typhoid, tuberculosis, syphilis, hepatitis (A, B, or C), influenza, and dengue (Satyanarayana et al. 2014). Although the number of glucose

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tests may be more than malaria because the home tests are unaccounted for and the widespread of the disease in India and all over the world (Ramachandran et al. 2001). The test for COVID-19 disease may now be the most tests being done using a biosensor.

1.3.1

POC Biosensors for Detection of Cardiovascular Diseases

Cardiovascular diseases are related to the heart and the vascular system. Myocardial infarction, heart failure, and acute coronary syndrome are the most common cardiovascular illnesses. By 2035, the American Heart Association (AHA) predicts that 45.1% of the population in the United States will have a cardiovascular disease. In 2016, the number of global death from cardiovascular disease was estimated to be 17.6 million (Benjamin et al. 2017; Ouyang et al. 2020). Biomarkers recommended for myocardial infarction and acute coronary syndrome are cardiac troponin I (cTnI), cardiac troponin T (cTnT), and creatine kinase myocardial band (CK-MB) (O’Gara et al. 2013; Jneid et al. 2017; Thygesen et al. 2018). The level of these biomarkers is elevated from the onset of the symptom till several days. Biomarkers for the diagnosis of heart failure include highly sensitive c-reactive protein, B-type natriuretic peptide (BNP), and N-type propeptide BNP (NT-proBNP) (Greenland et al. 2010). Other emerging biomarkers like copeptin, myoglobin, and myeloperoxidase can indicate myocardial infarction (Melanson et al. 2004; Mythili and Malathi 2015; Roffi et al. 2016). POC devices for cardiovascular diseases are either handheld or benchtop ones. The RDT biosensors can be categorized under the handheld biosensor system.

1.3.1.1

Handheld POC Biosensor Devices

There are three commercially available handheld POC devices: Roche’s Cobas h 232, Abbott’s i-STAT, and Philips’ Minicare I-20. Cobas h 232 is based on the principle of chromatography using gold nanoparticles. It can detect cTnT (0.04–2 ng/mL), myoglobin (30–700 ng/mL), NT-proBNP (0.06–9 ng/mL), and CK-MB (1–40 ng/mL) (Hex et al. 2018; Ouyang et al. 2020). The i-STAT uses the principle of electrochemical sensing where there are two sites for enzyme-linked immunosorbent assay (ELISA) using microchannels. It can detect ctnI (0.02–50 ng/mL), BNP (0.015–5 ng/mL), and CK-MB (0.6–150 ng/mL) (Martin 2010; Loewenstein et al. 2013; Ouyang et al. 2020). And, the Minicare I-20 is a handheld device by Philips that utilizes magnetic particles. The device can detect only cTnI for a range of 0.018–6.1 ng/mL (Kemper et al. 2017; Ouyang et al. 2020). All the assays need whole blood or plasma as sample with a volume in the range of 17–150 μL and generate results within a response time of maximum 12 min.

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Zhang et al. studied a label-free optical biosensor with photonic crystal to detect cTnI. The biosensor was able to detect cTnI with level as low as 0.1 ng/mL (Zhang et al. 2014). In another study, Shanmugam et al. created an electrochemical biosensor to detect cTnT using a ZnO nanoparticle with a detection limit of 0.1 pg/mL (Shanmugam et al. 2016). For the characterization of the biosensor’s response to cTnT, DC and AC-based electrochemical impedence spectroscopy was used. Another ZnO nanostructure-based label-free, multiplexed electrochemical biosensor was developed (Shanmugam et al. 2018). Human blood serum was used to detect cTnT, cTnI, and BNP, with a detection limit of 1 pg/mL.

1.3.1.2

RDT POC Biosensor Devices

Some qualitative readers do not need reader device and the result can directly be determined by viewing it with the naked eye. RapiCard InstaTest by Cortez Diagnostics, Nano-Check ND-CD301S and ND-CD402 by Nano-Ditech, and LifeSign by Princeton BioMeditech, CardioDetect by Renesa are some of the LFIA to detect cTnI, CK-MB, and Myo within the of 1.5–100 ng/mL (Ip 2010; Zrari and Mohammed 2016). They all work on the principle of lateral flow chromatographic assay based (LFIA) by use of specific bioreceptor for cTnI, CK-MB, and Myo. Most of the samples were whole blood/plasma sample with maximum response time or TTAT of 15–20 min (Pezzuto et al. 2019; Ouyang et al. 2020). LifeSign by Princeton BioMeditech detects cTnI (minimum 1.5 ng/mL), CK-MB (minimum 5 ng/mL), and Myo (minimum 50 ng/mL) (Audet et al. 2015; Ouyang et al. 2020). Figure 1.4 shows a LifeSign which is a cassette-based. If the analyte is present in the sample the line appears indicating its presence.

Fig. 1.4 An LFIA cassette of LifeSign for detection of cTnI, CK-MB, and Myo. The control proofs migration and performs test of dye conjugates. If no control the test is invalid (Biomeditech n.d.)

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Benchtop POC Biosensor Devices

Benchtop-based devices that can detect multiple biomarkers are comparatively smaller than the laboratory system with a smaller TTAT but still bigger than a handheld device and can sometime require an expert to operate the system. Most devices with multiparameter capabilities for cardiovascular diseases, that are available commercially, are based on immunoassays with antibodies as their biomarkers (Ouyang et al. 2020). The transduction unit is optical based, either fluorescence, chemiluminescence, or colorimetric transducer. The use of chromatographic assay is most common for antibody capture and gold nanoparticle to give optical results. A test line on a paper strip containing functionalized colloidal gold nanoparticles captures antibody and causes a colour shift to indicate the presence of an antibody. Multiple lines on the same strip or multiple strips on the same cartridge techniques have been used for multiple biomarker detection. Multiple fluorescent materials were used in the Fluoro-Check AMI 3 in 1 to detect different biomarkers (Juntunen 2018). The Triage Cardiac Panel based on microcapillary is used to test multiple biomarkers with different zones, where different reagents target biomarkers to produce fluorescent output (Lingervelder et al. 2019; Boeddinghaus et al. 2020). The Triage Cardiac Panel series has a better lower detection limit than the Nano-Check AMI series (Mojibi et al. 2018; Çelik 2019; Ouyang et al. 2020). This is because fluorescence assays are more sensitive as transduction element as compared to colorimetry. These devices have a TTAT of 15–20 min and need a sample volume of 75–800 μL.

1.3.2

POC Biosensor for Cholesterol Detection

Cholesterol level is also an important factor in the human body. It can be used to determine neurological as well as cardiological diseases. Higher level of cholesterol indicates cardiological illness and lower level can indicate anaemia and hyperthyroidism. The main bioreceptor for cholesterol is cholesterol oxidase. The use of an electrochemical biosensor to measure cholesterol levels in the blood was studied by Kaur et al. (2018). Platinum electrodes coated with thin layer of nickel oxide on the working electrode and bare platinum on the counter electrode were employed in microfluidic channels which were made of polydimethylsiloxane. Cholesterol oxidase was immobilized on the nickel electrode. With a range of 0.12–10.23 mM and a sensitivity of 45 A/mM/cm2, a limit of detection of 0.10 mM was achieved (Fig. 1.5). Kaur et al. (2017) developed another microfluidic channel using paper for the analysis of cholesterol. SU 8 photoresist was used to make the microfluidic channels (Kaur et al. 2017). Amperometric measurement is done when the cholesterol comes

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Fig. 1.5 Amperometric biosensor made of PDMS for the microfluidic channel to quantify cholesterol (Kaur et al. 2018)

Fig. 1.6 Colour change of the nanofiber mat with increased concentrations of cholesterol (Dhawane et al. 2019)

in contact with the cholesterol oxidase. The working and counter electrodes were made of graphite, while the reference electrode was comprised of silver and was treated with nickel oxide nanoparticles. The sensitivity achieved was 26 μA/mM/ cm2 with a range of 0.12–10.23 mM. Dhawane et al. reported a cholesterol-detecting optical biosensor utilizing chitosan nanofiber (Dhawane et al. 2019). Chitosan nanofiber mat was prepared using chitosan and polyvinyl alcohol (PVA) in a 0.7:1 (w/w) ratio. Cholesterol oxidase was immobilized on the chitosan nanofiber mat as a bioreceptor for the cholesterol. UV-Visible spectrophotometer is used for the colorimetric detection of the cholesterol level by determining the resultant H2O2 with a mixture of chromogenic substance (3,30 ,5,50 -tetramethylbenzidine hydrochloride). Different concentration ranging from 50 to 300 mg/dL was measured using the chitosan nanofiber mat (Fig. 1.6).

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Yang et al. investigated an electrochemical non-enzymatic biosensor for cholesterol detection (Yang et al. 2012). On a glass substrate, platinum nanoparticles and carbon nanotubes are alternatively deposited layer by layer, resulting in a total of 24 bilayers. A linear range of 0.005–10 mM was achieved with a very low detection limit.

1.3.3

POC Biosensors for Detection of Diabetes

Diabetes is a condition when the blood sugar is more than 3.5–5.5 mmol/L (Bunescu et al. 2013; Güemes et al. 2016). Biosensor for diabetes is one of the most widely used POC biosensors by patients themselves. The inability to produce insulin increases the blood sugar level. There are three generations of glucose biosensors. Amperometric enzymatic biosensing was the first generation of glucose biosensor with advantages like simplicity, miniaturization, and cheap (Karyakin et al. 1995; Wang 2001; Freeman et al. 2013). The resultant H2O2 solution from the reaction of glucose and glucose oxidase (bioreceptor) was measured electrochemically. The first-generation glucose biosensor had disadvantages. The first was the interaction of electroactive chemicals such as ascorbic acid, uric acid, and acetaminophen in the blood (Kulkarni and Slaughter 2016; Scholten and Meng 2018). This drawback was addressed by adding catalyst to H2O2, like Prussian blue or noble metal. The second drawback was oxygen deficit caused due to oxygen insolubility in the biological fluid. A diffusion limiting membrane was used to address this drawback by adjusting the flux of oxygen and glucose to the surface of the electrode (Abdel-Hamid et al. 1995; Matsumoto et al. 2001; Zhu et al. 2012). Another way to address this issue is to use oxygen-rich carbon past electrode (Wang and Lu 1998). In the first generation, the current of the reduction in O2 is measured amperometrically. The first-generation glucose biosensors are POC because of their miniature structure and simplicity to make the reading devices. In the second generation, the oxygen transfer is addressed by the use of mediators between the glucose oxidase and the electrode with materials. These materials make the transfer of electron faster and also solve the oxygen deficit problem in the first generation (Zhang et al. 2020). The third generation of glucose biosensor incorporates glucose oxidase directly with the electrode thereby eliminating the need of mediators for the transfer of electron (Koopal et al. 1994; Mehmeti et al. 2017). New development of electrodes based on nanomaterials like graphene, carbon nanotubes, etc., has improved the sensitivities and also overcomes the drawbacks of the first generation and second generation (Tang et al. 2000; Alwarappan et al. 2010; Fu et al. 2011). A non-enzymatic biosensor is mainly focused on an artificial enzyme that is made from nanomaterials (Gooding 2019). Teymourian et al. discussed three drawbacks of non-enzymatic biosensor, i.e. lack of specificity because of not using selective recognition element, alkaline pH of the solution and emphasis of research on the

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synthesis of nanomaterial and its fabrication instead targeting the glucose itself (Juska and Pemble 2020; Teymourian et al. 2020). Atanasov and Wilkins discussed about implantable glucose sensors with insulin pump for continuous monitoring of blood glucose using an electrochemical biosensor (Atanasov and Wilkins 1994). The device was implanted subcutaneously. The use of third-generation glucose biosensor made it easy to implant the device which could measure up to 500 mg/dL. Elsherif et al. also studied a photonic microstructure made using glucose selective hydrogel functionalized with phenylboronic acid (Elsherif et al. 2018). It was integrated with a contact lens. On contact with glucose the microstructure swells up and modulated Bragg’s diffraction is measured between zero order and first order using a smartphone camera. The sensitivity achieved was 12 nm/mM with a response time of maximum of 30 min. When associated with telemedicine frameworks, wireless systems and smartphone-based glucometer allows medicinal service suppliers to screen the physiological attributes of patients after therapeutics or medications (Weymouth et al. 2018). One of the most trending research studies is on non-invasive and wireless sensors. Glucose POC biosensors using infrared and Raman spectroscopy have now been developed which showed promising in contrast to the result from an invasive method (Buford et al. 2008; Sivaraman and Shankar 2016). A tattoo-based amperometric biosensor for glucose was used to monitor the blood glucose during and after eating food (Bandodkar et al. 2015). The limit of detection of the biosensor was 10 μM. The on-body test also showed specific spike in glucose as compared to the Accu-Chek Aviva Plus. The BeatO Glucometer is India’s first POC glucose metre that uses a smartphone to measure blood glucose levels (George et al. 2019; Mondal et al. 2020; Sabharwal et al. 2021). Although the ease of use in BeatO glucometer, the study by Mondal et al. found that the accuracy is 74% of the required clinical use regulation. Some other handheld POC glucometer includes Gluco One by Dr. Morepen, Accu-Chek, OneTouch, Dr. Trust, etc.

1.3.4

POC Biosensors for Detection of Kidney Diseases

Kidney is one of the most important organs to filter out toxins and waste materials from the human body. Kidney diseases may be acute or chronic with many biomarkers (Chawla and Kimmel 2012). Although serum creatinine and blood urea nitrogen are often used as biomarkers for detecting acute kidney illness, they are not sensitive enough and they may indicate other non-renal functions (Tesch 2010; Edelstein 2016, 2017). There are more sensitive and specific biomarkers like cystatin-c, beta trace protein, urine albumin, uric acid, neutrophil gelatinaseassociated lipocalin (NGAL), etc. (Nickolas et al. 2008; Fassett et al. 2011). The Nova Stat sensor POC and the ABL800 flex analyser are two well-known POC devices for measuring creatinine and estimating glomerular filtration rate (eGFR).

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The normal level of creatinine in the blood is 45–90 μM (male) and 60–110 μM (female) (Killard and Smyth 2000; Tseng et al. 2018). It is also present in urine (4.4–18 mM) (Ruedas-Rama and Hall 2010; Li et al. 2015), saliva (4.4–17 μM) (Lloyd et al. 1996; Venkatapathy et al. 2014), and sweat (9.4–18 μM) (Bass and Dobalian 1953; Al-Tamer and Hadi 1997). There are more studies of optical-based readout than electrochemical biosensing in previous studies (Cánovas et al. 2019). Dasgupta et al. studied the usage of ferric chloride as a creatinine receptor. With the increase in the creatinine, ferric chloride concentration decreases thereby reducing the current signal (Randviir and Banks 2013; Dasgupta et al. 2018). It has also been stated that a carbon paste electrode can be used on a sodium chloride solution. Singh et al. investigated the utilization of reduced graphene oxide, coated on a 3D printed silver electrode, with stabilized binary copper and iron oxide (Singh et al. 2021). It was a non-enzymatic sensor which was able to eliminate the interference of urea, glutathione, etc. It was however not a commercialized sensor but has a scope of POC biosensing. Snaith et al. compared Nova StatSensor, Abbott i-STAT, and Radiometer ABL800 FLEX with the Roche Cobas 8000 series as a reference and found that ABL800 FLEX had the best concordance with the reference, followed by Abbott i-STAT, and finally Nova StatSensor (Snaith et al. 2018). Progression of mild to moderate kidney disease can be predicted with Cystatin C level in blood serum (Onopiuk et al. 2015). It is also said to be more reliable than creatinine (Bleher et al. 2012). Devi et al. discussed the fabrication of electrochemical sensor with the modification of the carbon working electrode with graphene oxide-chitosan conjugated with anti-cystatin C antibody (Devi and Krishnan 2020). This can have application in POC because of the miniature size of the system. A disposable immunosensor was also developed which was made of gold nanoparticles conjugated with anti-cystatin C antibody which was fabricated using screen printing technology (Lopes et al. 2019). Bleher et al. reported the use of anti-cystatin antibody as bioreceptor in glass substrate to have a label-free optical biosensor to diagnose kidney diseases (Bleher et al. 2012). But, creatine is still the preferred biomarker over Cystatin C (Shlipak et al. 2013). Cystatin C has also been known to be used as a biomarker in diabetes retinopathy (Wong et al. 2015). Albumin in the urine is also an indication of renal failure. Huang et al. reported a biosensor made of microfluidic channels made of polydimethylsiloxane (Huang et al. 2007). The electrode materials were coated on a glass substrate. The limit of detection was found to be 5 ppm which was lower and better than the commercially available strips (Kouri et al. 2000; Huang et al. 2007). Smith et al. conducted an experiment on a commercially available Mission Urinalysis Reagent Strip (manufactured by Acon laboratories) (Smith et al. 2016). The strip provides colour change which could be analysed using simple software and a smartphone as demonstrated by Smith et al. The Mission® U120 Urine Analyzer and Ultra Urine Analyser are POC devices manufactured by Acon. Liu and Ma designed a new portable urine analyser which can meet the standard of The Mission® U120 Urine Analyzer and it can detect analytes like creatinine, microalbumin, ascorbic acid, etc. (Liu and Ma 2018).

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POC Biosensors for Detection of Cancer

Cancer is unwanted growth and uncontrolled rapid division of cells that can be benign as well as malignant. Some biomarkers for solid tumours are carcinoembryonic antigen (CEA) for colon, CA125 for ovarian, protein-specific antigen (PSA) for prostate, CA15-3 or CA27.29 for breast cancer (Soper et al. 2006). Antibodies are commonly used as recognition elements but there are other approaches like aptamers, peptides, and molecular imprinting of polymers (DeRoock et al. 2001; Cerchia et al. 2002; Chambers and Johnston 2003). Polyclonal and monoclonal antibodies are most common approaches for targeting the antigen. To target cells peptides have also been used as they are smaller in size and have high selective bond affinity to the binding sites of the cells. Aptamers are often created using the exponential enrichment process, which involves the systemic development of ligands. Optical, piezoelectric, and electrochemical transduction are often studied with these biorecognition elements. Mavrikou et al. developed a electrochemical POC-based biosensor for the determination of PSA in the blood serum (Mavrikou et al. 2018). Anti-PSA antibody was used as a biorecognition element by electroinserting it into vero cell. An 8-channel potentiostat was use used where all the three electrodes were screen printed with carbon, silver/silver chloride and the rest were ceramic substrate. Gold nanoparticles were used for amplification of the carbon working electrode. Khan et al. developed a biosensor to quantitatively determine the presence of PSA in saliva electrochemically (Khan et al. 2018). They used paper-based graphene nanoplatelets with diblock copolymer and gold electrode which showed a detection range of 0.1–100 ng/mL and the device gave results within 3–5 min.

1.3.6

POC Biosensors for Detection of COVID-19

The pandemic SARS-Cov2 has led to rapid production of antibody-based biosensors. With no effective medicine rapid and mass testing was the only solution, which could only be achieved by POC biosensor (Bahl et al. 2020). With the affinity of an antigen to the antibody, the SARS-Cov2 can be detected using the specific antibody (Samson et al. 2020). In 2020, Cepheid received emergency use authorization for the Xpert® Xpress SARS-CoV-2 test, which provided findings in 45 min. The principle of reverse transcriptase polymerase chain reaction (RT-PCR) was used and was therefore a quantitative determination of the pathogen (Vashist 2020). Abbott ID Now™ developed an isothermal nucleic acid amplification technology base detection unit that can quantify SARS-Cov-2. The result was given within 5 min time and moreover, due to its lightweight, it could be used as a POC device. A rapid LFIA biosensors-based sensing of IgG and IgM antibodies from blood serum/plasma was widely used in suspected patients. The test developed by

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BioMedomics, USA, could give the result in 10 min (Jamshaid et al. 2020). LFIAbased antigen test is one of the most carried out tests.

1.3.7

POC Biosensor for Detection of Other Diseases

Many other POC biosensors are available and commercially manufactured by different brands for various purposes. RDT LFIA for malaria is available in all primary healthcare centres in India (Singh et al. 2010, 2013). Vyas et al. compared the SD Bioline Malaria antigens test kit for the two types of malaria (plasmodium vivax and falciparum) with standard blood smear microscopy (Vyas et al. 2014). The sensitivity found for Plasmodium falciparum was 100% and for Plasmodium vivax it was 98.6%. The RDT was based on the principle of detection of antigens with the immunochromatography method in the blood from finger prick. Some detect only plasmodium falciparum, and some can detect all Plasmodium vivax, malariae, and ovale. Another kit available in the Indian market for malaria Plasmodium falciparum and Plasmodium vivax are Alere Trueline by Alere Medical, etc. Pardee et al. developed a biosensor for Zika virus made from inexpensive paper and claimed to be effective for early detection (Meagher et al. 2016; Pardee et al. 2016). Cluster regularly interspaced short palindromic repeats-associated protein 9 nuclease (CRISPR-Cas9) technology was incorporated with the paper to detect the ribonucleic acid (RNA) genome of the virus. The RNA of Zika virus is isothermally amplified and the virus was differentiated from the Dengue virus using the colorimetric method. CRISPR-Cas9 is then used to differentiate the American and African strain. Song et al. developed a reverse transcription-loop-mediated isothermal amplification (RT-LAMP) disposable cassette for the detection of zika virus from oral swab sample (Song et al. 2016). Symptomatic patients who have acquired Zika virus have 103–106 plaque-forming units (PFU). The sensitivity of this POC-based RT-LAMP was compared with a benchtop RT-LAMP where the device could detect 5 PFU as compared to 3 PFU in a benchtop device. Siemens’ Rapidlab 1200 is a portable blood gas analyser that may be used in the field as a POC device (Ali et al. 2013; Kaushik et al. 2014). POC biosensors are already used widely for various diseases. Qualitative POC tests are easier to achieve than quantitative POC test. Paper-based sensors for distance-based measurement have also seen applications in the medical field. Haematocrit measurement of the red blood cells (RBC) in the blood was done by Berry et al. using a simple distance-based calculation with a paper (Berry et al. 2016; Frantz et al. 2020). Although the sensitivity of the assay is at its prime stage as the assay was semi-quantitative. The distance travelled by the RBC cannot directly correlate to the haematocrit and also coagulants affect the flow of RBC through the channel.

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15

Challenges and Future Prospects

For a POC biosensor parameters like high specificity, high sensitivity, accuracy, and long storage time are highly desirable. With the use of specific bioreceptors to biomarkers, the specificity can be achieved. Sensitivity requirements directly relate to the LOD of a biosensor. Since biomarkers in the biological samples are of trace quantity in some diseases, achieving the required sensitivity is still a challenge. Label-free electrochemical biosensors with semiconductor technology are considered to be highly reproducible, accurate, and can be used for real-time analysis (Chen et al. 2020). But there is an issue of lower specificity in label-free. Labelled biosensors have more specificity and sensitivity and can be more reliable for clinical analysis (Sin et al. 2014). Climatic conditions like temperature, pressure, and humidity may also affect the parameter along with the stability of the POC biosensor. An example of the effects temperature in a paper-based micro-calorimetric biosensor for glucose estimation was studied by Davaji and Lee (2014). The heat loss to the surrounding (based on the thermal conductivity) affects the output of the sensor because in the calorimetric method heat generated is measured. Therefore, with time the output will reduce due to quasi-adiabatic conditions. Proteins and other biological products are also affected by temperature which are used as bioreceptor in POC biosensors. These climatic conditions are there for directly linked to the decline of the required parameters like loss of sensitivity. Another challenge of a POC biosensor is clinical analysis. If the result is not interpreted by a certified physician, treatment cannot be given. One solution to this is, if a POC platform (the transducer) is connected to a smartphone through various non-wired modalities like a Bluetooth, zigbee, and near field connection (NFC), the results can be communicated to a doctor or a certified physician (Kassal et al. 2018). There is also a lack of regulatory boards in most developing nations which leads to the use of sub-standard POC test devices which were mainly seen for malaria test kit (Peeling and Mabey 2010; Drain et al. 2014). The requirement of a specific regulatory board of POC devices will help advocate the use of tests and treatment. Engel et al. found pricing and the relation between the patient and doctor also is a barrier for POC testing in India (Engel et al. 2015). Miniaturization is the way forward for POC biosensor devices in healthcare. Microelectromechanical systems (MEMs) are one method of miniaturization of a biosensor. But for MEMs the fabrication cost can be very high making the biosensor expensive (Derkus 2016). The main concern is the cost of fabrication and achieving an environmental friendly material (Mejía-Salazar et al. 2020). Paper-based biosensor reduces the cost of fabrication and is used in both optical and electrochemical type of biosensor (Shergujri et al. 2019). Paper is biodegradable therefore making it environmentally friendly. There are many ways of fabricating microfluidic channels in a paper further reducing the cost of the biosensor. Application of paper base microfluidic biosensors is already used for the detection of various diseases like the

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qualitative analysis using LFIA. But for quantitative readouts, a transducer is needed for colorimetric, luminescence, and electrochemical detection.

1.5

Conclusions

In the healthcare sector, biosensors are required for diagnosis and monitoring of different diseases and ailments with enhanced sensitivity and accuracy near the patients. POC-based biosensors have been used to determine various analytes, like pathogens, proteins, nucleic acids, and glucose, for the identification of a host of ailments or sicknesses, as well as malignant growth of tumours (Inan et al. 2017; Syedmoradi et al. 2017). Most diseases can be determined with either the presence of a biomarker or elevation in biomarker contained in the biological materials of the human body. POC biosensor devices are advantageous where there is no sophisticated laboratory equipments and experts to operate them. POC biosensor also gives a significant TTAT which reduces the time the patient gets the actual treatment. With the increase in diabetes worldwide, the need of POC device was urgent in the 1970–1980s which gave birth to POC biosensing for dipstick urine-based colorimeter and blood-based glucometer (Mazzaferri et al. 1970; Sönksen et al. 1978). LFIA (RDT) is also a common application of POC biosensor where qualitative results of diseases are quickly determined. Pregnancy test, malaria test, and even the coronavirus disease 2019 current used LFIA RDT. Paper-based LFIA and non-LFIA biosensors are more widely used because of the cost-effectiveness. Cost-effectiveness of a POC biosensor comes as a result of low-cost material, simple fabrication, and ease of functionalization (Choi 2020). Sensitivity and selectivity of biomarkers are very specific to the bioreceptors making the margin of error very less probable with ideally no false result.

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Chapter 2

An Overview of Biomolecules Used in the Development of Point-of-Care Sensor Girish Chandra Mohanta and Satish Kumar Pandey

2.1

Introduction

The field of biosensor was first introduced in 1962 by Clark and Lyons with their invention of “glucose biosensor” by immobilizing the glucose oxidase enzyme on the surface of oxygen. The biosensor provided a specific and selective response to glucose concentrations sensed by the immobilized enzyme and transduced into a measurable signal by oxygen electrode (Clark Jr and Lyons 1962). Since then, the biosensors fields have grown at an exponential pace. According to IUPAC, a biosensor is a self-integrated, compact system, capable of providing quantitative or semi-quantitative information about its target analyte in a highly sensitive and specific manner (Thévenot et al. 1999, 2001). The biosensor consists of different components such as biorecognition element which is in direct spatial connection with a transducing element. The transducing element is capable of sensing minute physico-chemical changes occurring during biorecognition molecule-analyte interaction and relays it as a measurable output signal. The information of the output signal is then processed and reported as readable data in the form of digital display and print-out of color/spectral change. The overall goal of a biosensor is to combine and utilize the high specificity of biomolecules with high sensitivity of different transducing elements, so different analytical purposes in various fields (Carpenter et al. 2018). In the past few decades, biosensors have already revolutionized various fields such as medical diagnostics, process control, agriculture and environmental monitoring, quality control, defense, pathogen screening, drug discovery, mining,

G. C. Mohanta Material Science and Sensor Applications (MSSA) Division, CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh, India S. K. Pandey (*) Department of Biotechnology, School of Life Sciences, Mizoram University (Central University), Aizawl, Mizoram, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 M. Gogoi et al. (eds.), Nanobiosensors for Point-of-Care Medical Diagnostics, https://doi.org/10.1007/978-981-19-5141-1_2

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Biosensor

Bio components

Antibody

Enzyme

Nucleic Acid (DNA/RNA )

Transducer

Optical

SPR

Enzymatic

Electrochemical

NPs / Color beads

Amperometry Potentiometry

Conductometry Protein

Phage

Fig. 2.1 Components of a sensor comprising biological receptors, transducers, and detectors

and several more. A schematic of a complete biosensor system is illustrated in Fig. 2.1. In recent times, significant developments in the field of miniaturized electronic and optical components, rechargeable and potable power sources, and low-cost fabrication techniques have fueled the next phase in the field of biosensor development of so-called “point-of-care (POC)” biosensors (Kaushik and Mujawar 2018). The POC biosensors have tremendous potential in disease prognosis and diagnosis, status monitoring in hospital emergency setups, and facilitating penetration of healthcare services to remote regions and resource-constraint countries. As compared with traditional laboratory-based setups, POC biosensors require very small amount of sample and reagents, have rapid turn-around times, and offer significant improvement in potability and ease-of-operations (Patel et al. 2016). Furthermore, emerging technological innovations have now enabled the next generation of POC biosensors which offers self-testing capabilities for the patient without any requirement of hospital visit. The result could also be shared wirelessly with the healthcare provider (e.g., doctor) through internet. Going one step ahead, efforts are now being made in realizing mobile-based and wearable POC biosensors. These biosensors are being developed as standalone internet-of-things (IoT) system or smartphone-based platform which is capable of measuring target analyte in collected samples and directly communicate the results to clinician and patient through wireless

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communication (Noah and Ndangili 2019). Efforts are also being made toward development of wearable biosensors capable of sampling and measuring analyte directly on the body (Kim et al. 2019b). These smartphones and wearable POC biosensor systems typically require combination and integration of highly complex network of various components such as sampling platform, biorecognition element, enzymes, oligonucleotide, transducing elements, integrated power source, signal processing and read out, and various potable or wearable form factors (Shrivastava et al. 2020). One of the critical components of biosensors is its biorecognition element which is usually a biomolecule responsible for providing sensor specificity. It does so by facilitating highly specific binding to the target analytes under optimized conditions. Various types of biomolecules have been used as the recognition element in POC biosensors which can be broadly categorized according to their chemical nature such as peptides, proteins, nucleotides, glycans, and whole cells. This chapter is aimed at providing a brief overview of various biomolecules utilized in POC biosensors.

2.2

Proteins

Proteins are perhaps the most versatile and abundantly utilized class of biomolecules for the recognition of target analytes. Several different types of proteinaceous molecules ranging from simple peptides to more complex antibodies, enzymes, multienzyme complexes, and lectins are utilized in biosensors.

2.2.1

Peptides

Peptides are constituted from short repeats of natural or synthetic amino acids joined together by peptide bonds similar to that of a natural protein. Thus, with appropriate sequence, peptides are able to work as a functional substitute for more complex and bulky proteins. For example, as a functional substitute of enzymes itself, peptides provide a continent tool for screening of enzyme inhibitors (Zozulia et al. 2018). Furthermore, by tuning the physico-chemical properties of peptides, supramolecular assemblies like tubes, strips, bilayers, micelles, and fibers can be easily obtained. This supramolecular assembly of peptides is driven by the non-covalent interactions such as electrostatic, hydrophobic, and van der Waals interactions (Ekiz et al. 2016). In biosensor applications, peptides are utilized as biorecognition elements dues to their excellent stability against denaturation, high specificity, low cost and ease of preparation, facile modification, tunable and versatile chemical properties, and high affinity toward target analyte. Till date, peptide-based biosensors have been developed for various analytes ranging from simple metal ions, volatile organic compounds, pollutants to more complex proteins, enzymes, antibodies nucleotides, and whole cells (Karimzadeh et al. 2018). For example, Kim et al. have reported a

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peptide-based POC electrochemical biosensor for sensitive detection of dengue virus (DENV) (Kim et al. 2019c). The peptide was synthetically developed against dengue virus non-structural (NS1) protein antigen and immobilized on the gold sensor surface. The specific interaction between the peptide and antigen was probed by square wave voltammetry (SWV) and electrochemical impedance spectroscopy (EIS) techniques. The sensor exhibited high stability and sensitivity with a limit of detection (LOD) of 1.49 μg/mL. Recently, antimicrobial peptides (AMPs) have gained tremendous research attention due to their potential applications in broad-spectrum antimicrobial activity, immunomodulatory effects, and therapeutic value (Mahlapuu et al. 2016). These natural peptides are generally short, positively charged, and exhibit broad-spectrum antimicrobial activity either through directly disrupting the bacterial membrane or via modulating the host immune system. Furthermore, their excellent binding affinity makes them potential biorecognition element in biosensors (Hoyos-Nogués et al. 2018). For example, Wilson et al. described a POC electrochemical biosensor for single step, low cost, and sensitive detection of several pathogenic microorganisms including E. coli, S. aureus, and S. typhi in potable water and fruit juice using antimicrobial peptide melittin (MLT) (Wilson et al. 2019). Another potential application of peptides is their application in fabricating “Bioelectronic Nose” for the detection of various volatile organic compounds (VOCs) (Barbosa et al. 2018). The composition and quantitative detection of various VOCs emanating from livestock and fish could be easily correlated with their freshness. For example, the quantitative information of trimethylamine (TMA) emission during microbial spoilage of fish and other seafoods can be considered as its freshness indicator. Accordingly, Lee et al. have reported a single-walled carbon nanotube (SWCNT)-based field effect transistor (FET), an electrochemical biosensor for ultrasensitive detection of TMA to ascertain the freshness quality of oysters (Lee et al. 2015). They utilized olfactory receptor-derived peptides (ORPs) as biorecognition probes which enabled parts per trillion (ppt) level sensing in real time.

2.2.2

Enzymes

The use of enzymes as biorecognition element is perhaps the most representative and most studied among the various classes of biosensors. Particularly, oxidoreductase class of enzymes has been extensively utilized for fabricating POC electrochemical biosensors against various clinical and environmental analytes (Dzyadevych et al. 2008; Bollella and Gorton 2018). Several of these electrochemical biosensors have been already marketed as successful POC sensor devices (Kucherenko et al. 2019). The most successful among them is the glucose biosensor whose market value is exponentially increasing due to the rise in the global burden of diabetes (Yoo and Lee 2010).

2

An Overview of Biomolecules Used in the Development of Point-of-Care Sensor

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The oxidoreductase class of enzymes catalyzes the transfer of electrons from a reductant to the substrate bringing about an oxidation-reduction reaction. Consequently, these enzymes are highly suitable for integration into an electronic device which could sensitively detect the electron flow (amperometric) or potentially generated (potentiometric) during the enzyme-analyte interaction (Karunakaran et al. 2015; Bollella and Gorton 2018). Traditionally this has been achieved by fabricating an enzyme electrode by directly immobilizing the enzyme over the electrode surface. For example, a glucose-specific enzyme electrode was first reported by Clarke and Lyon in 1962 (Clark Jr and Lyons 1962). They immobilized a glucose oxidase enzyme layer over the oxygen electrode and monitored the consumption of oxygen during the enzyme-catalyzed reaction. GODðoxÞ þ Glucose ! Gluconolactone þ GODðredÞ GODðredÞ þ O2 ðdissolvedÞ ! GODðoxÞ þ H2 O2 The peroxide generated during the regeneration step was measured amperometrically at the anodic potential of +0.6 V (vs. Ag/AgCl). However, the sensitivity of these early generation glucose biosensors was always dependent on the amount of dissolved oxygen. Furthermore, electroactive components in the blood such as uric acid were a frequent interferent in these studies. To overcome these issues, the second generation of enzyme electrodes utilized a secondary electron mediator for efficient transfer of electron to the electrodes. This also enhanced the sensitivity of the biosensors. For example, Cess and co-workers utilized such as ferrocene as the electron mediator which significantly improved the sensitivity and stability of the biosensor (Cass et al. 1984). Furthermore, by utilizing graphite as electrode material, Cess and co-workers reported the first printable enzyme electrode which was commercialized by the US MediSense company in 1987. The sensing reaction in presence of mediator modifies to: GODðoxÞ þ Glucose ! Gluconolactone þ GODðredÞ GODðredÞ þ MðoxÞ ! GODðoxÞ þ MðredÞ MðredÞ ! MðoxÞ þ nHþ þ ne The electron released during regeneration of the mediator is detected amperometrically. The next stage of enzymatic biosensor development was fueled by the application of conducting polymers as the electron transfer medium (Lakard 2020). Pioneering work of Shirakawa, MacDiarmid, and Heeger in this field paved the development of several different conducting polymers, which earned them the Nobel Prize in Chemistry in 2000 (Shirakawa et al. 1977). These polymers are constituted from alternating single (σ) and double (π) bonds and with delocalized π electrons across their entire structure by the virtue of which, polymer can easily undergo reversible oxidation-reduction reactions. Conducting polymer combines the high degree of

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G. C. Mohanta and S. K. Pandey

flexibility of polymers amenable for device fabrication while maintaining the excellent conductivity of conventional semiconductor materials. Biosensor devices fabricated using conduction polymers exhibited improved sensitivity, low cost, higher processability, and longer functional stability (Aydemir et al. 2016). For instance, Dong et al. utilized Nafion (a sulfonated tetrafluoroethylene-based fluoropolymercopolymer) for immobilizing ferrocene and glucose oxide on the electrode surface. Because of the hydrophilic and hydrophobic nature of the Nafion, the enzyme and ferrocene mediator are retained within the polymer, thus increasing the stability and shelf-life of the biosensor (Dong et al. 1992). The incorporation of nanomaterials in the sensing layer is another promising trend which is recently emerging (Kucherenko et al. 2019). The physico-chemical properties of nanomaterials are vastly different from their bulk counterpart because of the quantum confinement effect at such a scale (